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health interfaces, helping to improve user engagement, health outcomes, and system efficiency. Artificial intelligence (AI) will be investigated as both a tool to assess the quality of user interface and
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to the development and implementation of approaches that interface with living systems through novel materials and algorithms, electric and magnetic fields, ultrasound, optics and targeted radiation, microfluidics
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of this joint laboratory is towards the development of innovative nanotechnologies and nanomaterials for various electronic and photonic applications. For more details, please view https://www.ntu.edu.sg/cintra
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materials systems at the molecular level with machine learning. The PhD Student will work with tumour sections to develop multiple instance learning and weak supervision / spatial transcriptomics models
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local and long-range mobility under catalytically relevant conditions, providing a rigorous research environment at the interface of catalysis, materials chemistry, and computational modeling. Duties
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to apply Website https://www.jobbnorge.no/en/available-jobs/job/297933/phd-candidate-in-ai-nativ… Requirements Research FieldComputer scienceEducation LevelMaster Degree or equivalent Research
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the consortium Your Profile: Excellent Master and subsequent PhD in computer science, engineering, biophysics, applied mathematics, computational biology or a related field Proven programming expertise in Python
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the interface of plasma physics, quantum electrodynamics, and computational modeling. Your qualifications PhD degree in physics Knowledge of laser-plasma physics Theory and modelling of ultra-intense laser-matter
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-based materials/devices, bioelectronic microsystems, unconventional computing, liquid crystals and nanomaterials for applications such as thermal management, neural interfaces, energy harvesting and
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on model surfaces In situ and operando (surface) X-ray scattering studies of catalyst/polymer interfaces Design, optimization, and testing/benchmarking of reactors for in situ and operando studies